Evidence map›Paper›PMID 41659498›Full record

ArticlebioRxiv : the preprint server for biology2026

The Extremely Brilliant Brain: An Isotropic Microscale Human Brain Dataset.

Matthieu Chourrout, Andrew Keenlyside, Eric Wanjau, Yael Balbastre, Ekin Yagis, Joseph Brunet, David Stansby, Klaus Engel, Xiaoyun Gui, Julia Thönnißen and 7 more

Abstract readPreprint
In one paragraph

Article in bioRxiv : the preprint server for biology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

17 authors.

Matthieu ChourroutDepartment of Mechanical Engineering, University College London, Gower Street, London, WC1E 6BT, United Kingdom.ORCID 0000-0002-2282-6976
Andrew KeenlysideDepartment of Mechanical Engineering, University College London, Gower Street, London, WC1E 6BT, United Kingdom.ORCID 0000-0002-6059-2103
Eric WanjauDepartment of Mechanical Engineering, University College London, Gower Street, London, WC1E 6BT, United Kingdom.ORCID 0009-0007-5989-129X
Yael BalbastreDepartment of Experimental Psychology, University College London, Gower Street, London, WC1E 6BT, United Kingdom.ORCID 0000-0001-8758-9978
Ekin YagisDepartment of Surgery & Cancer, Faculty of Medicine, Imperial College London, 1A Sheldon Square, London, W2 6PY, United Kingdom.ORCID 0000-0003-3510-3141
Joseph BrunetDepartment of Mechanical Engineering, University College London, Gower Street, London, WC1E 6BT, United Kingdom.ORCID 0000-0002-8424-9510
David StansbyDepartment of Mechanical Engineering, University College London, Gower Street, London, WC1E 6BT, United Kingdom.ORCID 0000-0002-1365-1908
Klaus EngelSiemens Healthineers, Siemensstrasse 3, Forchheim, 91301, Germany.ORCID 0009-0001-1423-898X
Xiaoyun GuiInstitute of Neuroscience and Medicine, Forschungszentrum Jülich, Wilhelm-Johnen-Straße, Jülich, 52428, Germany.
Julia ThönnißenInstitute of Neuroscience and Medicine, Forschungszentrum Jülich, Wilhelm-Johnen-Straße, Jülich, 52428, Germany.
Timo DickscheidInstitute of Neuroscience and Medicine, Forschungszentrum Jülich, Wilhelm-Johnen-Straße, Jülich, 52428, Germany.ORCID 0000-0002-9051-3701
Laurent LamalleUMS IRMaGe CHU Grenoble, Université Grenoble Alpes, Bâtiment Edmond J. Safra, Chemin Fortune Ferrini, La Tronche, 38700, France.ORCID 0000-0002-8930-7337
Alexandre BellierDepartment of Anatomy (LADAF), Université Grenoble Alpes, CIC Inserm 1406, Chemin Duhamel, La Tronche, 38700, France.ORCID 0000-0003-0907-0315
Umesh VivekanandaInstitute of Cognitive Neuroscience, University College London, 17 Queen Square, London, WC1N 3AZ, United Kingdom.ORCID 0000-0001-6116-2335
Paul TafforeauEuropean Synchrotron Radiation Facility, 71, Avenue des Martyrs, Grenoble, 38000, France.ORCID 0000-0002-5962-1683
Peter D LeeDepartment of Mechanical Engineering, University College London, Gower Street, London, WC1E 6BT, United Kingdom.ORCID 0000-0002-3898-8881
Claire L WalshDepartment of Mechanical Engineering, University College London, Gower Street, London, WC1E 6BT, United Kingdom.ORCID 0000-0003-3769-3392

Funding

BRAIN CONNECTS: The center for Large-scale Imaging of Neural Circuits (LINC)UM1NS132358 · NINDS · MASSACHUSETTS GENERAL HOSPITAL · PI Suzanne N Haber, Elizabeth M. C. Hillman · 2023 to 2026
$17.5M
NIMHD NIH HHS L32 MD001290NINDS NIH HHS UM1 NS132358
6 · The paper itself

Abstract

We present an isotropic 7.72 μm/voxel post-mortem human brain dataset acquired using Hierarchical Phase-Contrast Tomography (HiP-CT) at the ESRF Extremely Brilliant Source, beamline BM18. This fills a critical gap between whole-brain MRI at 100 μm resolution and serial-section histological reconstructions at 20 μm or finer. HiP-CT contrast, derived from X-ray phase shifts, enables rich 3D visualisation of complex neuroanatomy including white-matter bundles, microvasculature, and sub-nuclei. We provide open-source workflows for online data exploration, subvolume download, segmentation, and reintegration of analyses into the full dataset. We demonstrate the potential of this resource by tracing vasculature over long distances, segmenting nuclei, and extracting white-matter orientations with 3D structure-tensor analysis. High-resolution human brain datasets are transformative for quantitative neuroanatomy, circuit mapping, and validation of clinical imaging; this openly available resource is a critical step for global access to next-generation multiscale brain imaging.

Indexed as

magnetic resonance imagingneurovascularreferencewhite matterx-ray tomography

Identifiers

PMID41659498
PMCPMC12874060

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.